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An immune inspired approach to 802.11 Wireless LANs coverage optimization
2010 International Conference on Information, Networking and Automation (ICINA)
Year: 2010 | Conference Paper |
Coverage optimization is a critical issue in 802.11 Wireless LANs planning problems. In this paper an immune network algorithm named opt-aiNet is studied in order to automatize the planning process by optimizing the BS's (Base Station) sites. Compared the results of opt-aiNet and genetic algorithms(GA) which have been used in radio coverage optimization before, we found that opt-aiNet could find t...Show More
Multi-objective robust optimization based on NSGA-II and degree of robustness¯
2010 8th World Congress on Intelligent Control and Automation
Year: 2010 | Conference Paper |
Cited by: Papers (1)
This paper presents an approach to search robust optimal solutions with the concept of degree of robustness in multi-objective optimization problems. The definition of the degree of robustness is used in the calculation of the mean effective objective function(feff(X)) and in the evolutionary process, degree of robustness is considered as a factor to select robust solutions which can meet the dema...Show More
IPSO: An immune based PSO supervised learning system for incremental learning
2010 8th World Congress on Intelligent Control and Automation
Year: 2010 | Conference Paper |
Cited by: Papers (2)
PSO has been proved as an effective supervised learning system in recent years, but it's not an effective method for incremental learning problems. Aiming at the incremental learning target for classification, a hybrid algorithm of Particle Swarm Optimization (PSO) and Artificial Immune System (AIS) called Immune based PSO (IPSO) is presented in this paper. IPSO inherits the incremental learning a...Show More
Multiobjective evolutionary algorithm based on the Pareto Archive and individual migration
2008 7th World Congress on Intelligent Control and Automation
Year: 2008 | Conference Paper |
Cited by: Papers (1)
A multiobjective evolutionary algorithm based on the parallel evolution of multiple single objective populations and Pareto archive population is proposed. For each single objective population, single objective evolutionary algorithm is applied to optimize separately each of multiobjective functions, where individuals generated by tournament selection from the union of single objective and Pareto ...Show More
Chaos-Genetic Algorithm for Multiobjective Optimization
2006 6th World Congress on Intelligent Control and Automation
Year: 2006 | Conference Paper |
Cited by: Papers (3)
Chaos-genetic algorithm (CGA) combining local chaotic search and nondominated sorting genetic algorithm for multiobjective optimization is proposed. The method is composed of two stages. The wide search with nondominated sorting genetic algorithm (NSGA-II) is performed at the first searching stage, then the local search with chaotic mutation is performed at the second stage. Moreover, we cancel th...Show More
Stabilizing the Unstable Periodic Orbits via Improved Delayed Feedback Control for Discrete Chaotic Systems
2006 6th World Congress on Intelligent Control and Automation
Year: 2006 | Conference Paper |
Delayed feedback control (DFC) is a powerful method for stabilizing unstable periodic orbits embodied in chaotic attractors, but it has an odd number limitation, that is DFC can never stabilize a target unstable periodic orbit of a chaotic system if the transition matrix of the linearized system around the unstable periodic orbit has an odd number of real eigenvalues greater than unity. In this pa...Show More
Controlling Chaos using Differential Geometric Method with Delayed Variables
2003 4th International Conference on Control and Automation Proceedings
Year: 2003 | Conference Paper |
Differential geometric method with delayed variables is proposed to control chaotic systems to any desired periodic orbits. The delay time constant is chosen to be equal to the period of desired periodic orbits. The control can be achieved even with large noise; moreover, the converging speed of error is very fast. To demonstrate the feasibility of our proposed method, a Rössler system under diffe...Show More
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